A novel method for computing the minimum spanning tree and solution based on Cellular Neural Networks implemented on digital platforms

Author

Trong Tuan Do ; Chedjou, J.C. ; Fasih, Alireza ; Kyamakya, K.

Author_Institution

Fac. of Electron. & Telecommun., Hanoi Univ. of Technol., Hanoi, Vietnam

fYear

2009

fDate

20-21 July 2009

Firstpage

1

Lastpage

7

Abstract

We present a novel method for transforming graph theoretical problems into optimization problems and computing the minimum spanning tree (MST) of weighted and undirected graphs. The computing using Cellular Neural Networks (CNN) is considered for ultra-fast solutions when dealing with graphs of complex topology. As proof of concepts of the proposed method, simulations are performed on graphs of magnitude 11 and degree 8. The results obtained show the efficiency of the novel method.

Keywords

cellular neural nets; graph theory; graphs; optimisation; tree searching; cellular neural network; complex topology; graph theoretical problem; minimum spanning tree; optimization problem; undirected graphs; Cellular neural networks; Computational modeling; Computer networks; Electronic mail; Lagrangian functions; NP-hard problem; Optimization methods; Telecommunication computing; Telecommunication network topology; Tree graphs; Cellular Neural Networks; Lagrangian Relaxation; Minimum Spanning Tree; Multivariate Optimization; NP-hard Problems;

fLanguage

English

Publisher

ieee

Conference_Titel

Nonlinear Dynamics and Synchronization, 2009. INDS '09. 2nd International Workshop on

Conference_Location

Klagenfurt

ISSN

1866-7791

Print_ISBN

978-1-4244-3844-0

Type

conf

DOI

10.1109/INDS.2009.5227960

Filename

5227960